Wavelet Analysis of Northeastern United States Climate Data
Datum
2017
Autor:innen
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Verlag
University of Oregon
Zusammenfassung
Climate change has been an intensely debated topic over the last decade, and ways of detecting and quantifying climate change are necessary for informing the development of policies related to responses to climate change. Recent research in climate science has used the technique of climate indexing to represent data. Climate indexing averages multiple metrics to provide a better overall measure of regional climate. We present the uses, limitations, and results of applying wavelet transforms to climate indexed data taken from the Northeastern United States. We analyzed three individual metrics (maximum and minimum temperature, precipitation) along with the index metric (average of the three metrics). Monte Carlo simulations suggest that wavelet transforms will return nearly identical results when applied to raw data versus z-scored data, given sufficiently large data sets. Our results suggest that wavelet transforms are a useful tool for characterizing time-dependent climate behavior, but it is likely more useful to consider raw data than transformed data to give statistically reliable results.
Beschreibung
59 pages. A thesis presented to the Department of Physics and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, Summer 2017
Schlagwörter
Climate, Wavelet, Northeast United States, Data analysis, Physics, Math